Method and apparatus for prediction of post-operative perceived iris color

ABSTRACT

The present invention predicts prior to a laser iris color-change procedure what a patient&#39;s iris color will be after the procedure. The present invention does so by identifying and measuring a variety of anatomical features of the patient&#39;s eye that affect or are otherwise relevant to predicting the patient&#39;s post-operative iris color, translating these measurements into a post-operative iris color prediction, and communicating this prediction to the patient in a manner sufficient to manage the patient&#39;s expectations with respect to the aesthetic outcome of the procedure.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.16/631,435, filed Jan. 15, 2020, which is the national phase entry ofPCT Application No. PCT/GB2017/052410, filed on Aug. 16, 2017, which isa continuation-in-part of PCT Application No. PCT/IB2016/054907, filedAug. 16, 2016. The content of the foregoing applications is incorporatedherein in its entirety by reference.

BACKGROUND OF THE INVENTION

The mechanisms behind iris color are surprising for at least a couple ofreasons. First, under every brown iris is a blue or green iris. If thebrown pigment is removed, the underlying green or blue iris is revealed.Second, a green or blue iris is not actually green or blue. Instead, thevisible light entering the iris is scattered by the gray iris fibersinto the light's various wavelengths (i.e., colors or, morespecifically, hues). The shorter wavelengths (blue and, in some cases,green) bend and backscatter, mixing to varying degrees with thereflected light of the gray iris fibers, and creating the appearance ofa blue or green iris. The longer wavelengths (red, orange, yellow, and,in some cases, green) are absorbed by the thick layer of pigment on theback of the iris (known as the Iris pigment epithelium or “IPE”) beforethey have the opportunity to bend and backscatter. As a result, only theblue or green light is visible. U.S. Pat. Nos. 6,306,127 and 8,206,379disclose a procedure for altering the perceived color of a pigmentediris of a patient's eye. This procedure comprises applyingelectromagnetic radiation to the anterior iris surface, therebyinitiating the reduction and/or elimination of the stromal pigmentcovering all or a portion of such surface. Once this pigment is reducedand/or eliminated, white light is able to enter the iris and backscatterto create the appearance of a blue or green iris.

Patient satisfaction is an important feature of any medical procedure.In the case of aesthetic procedures, patient satisfaction depends inlarge part upon the ability of the physician to manage the patient'sexpectations by providing the patient with a reasonably accurateprediction of the aesthetic outcome of the procedure. In the case oflaser eye-color change, prediction is complicated by the occlusion ofthe stromal fibers by the stroma pigment. One option would be to performthe procedure on a small area of the iris behind the upper eyelid.Unfortunately, this is unlikely to provide an accurate prediction ofpost-operative color because a relatively large area of stromal fiberexposure is required to generate backscatter sufficient for a reasonablyaccurate prediction. Moreover, if any portion of the iris were treatedand the patient were to decide, based upon the predicted outcome, not toproceed with the procedure, the patient would be left with a permanentlydiscolored area on the iris (aka sectoral heterochromia).

There is therefore a need for a method and/or apparatus capable ofpredicting with reasonable accuracy, prior to a laser iris color-changeprocedure, what the patient's iris color will be after the procedure isperformed and the stromal pigment has been reduced and/or eliminated.

BRIEF SUMMARY OF THE INVENTION

The present invention predicts, prior to a laser iris color-changeprocedure, what a patient's iris color will be after the procedure. Thepresent invention does so by identifying and measuring a variety ofanatomical features of the patient's eye that affect or are otherwiserelevant to predicting the patient's post-operative iris color, derivinga post-operative iris color prediction from these measurements, andcommunicating this prediction to the patient in a manner sufficient tomanage the patient's expectations with respect to the aesthetic outcomeof the procedure. A preferred method of identifying and measuring atleast some of the anatomical features of the patient's eye is to usespecialized imaging and measurement devices and techniques, such asinfrared iris transillumination. A preferred method of translating thesemeasurements into a post-operative iris color prediction is to constructa database of these measurements and their associated iris colors fromthe relevant population pool and then compare the measurements collectedfrom the patient with the measurements contained in the database toreturn a predicted iris color for the patient. Finally, a preferredmethod of communicating the predicted iris color to the patient is togenerate an image of the patient's face, replacing the patient'spre-operative iris color with the predicted iris color (or colors, ifmore than one result is returned from the database search).

Other objects, features, and advantages of the present invention willbecome apparent upon consideration of the following detailed descriptionand the accompanying drawings in which like reference designationsrepresent like features throughout the figures.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 shows an embodiment of a data map of a patient's perceived iriscolors, featuring numbers to indicate colors.

FIG. 2 shows an embodiment of a visual map of a patient's iris colors.Note that FIG. 2 is a gray scale image, so it only approximates the truecolor variations of the embodiment.

DETAILED DESCRIPTION OF THE INVENTION

The mechanisms behind iris color are surprising for at least a couple ofreasons. First, under every brown iris is a blue or green iris. If thebrown pigment is removed, the underlying green or blue iris is revealed.Second, a green or blue iris is not actually green or blue. Instead, thevisible light entering the iris is scattered by the gray iris fibersinto the light's various wavelengths (i.e., colors or, morespecifically, hues). The shorter wavelengths (blue and, in some cases,green) bend and backscatter, mixing to varying degrees with thereflected light of the gray iris fibers, and creating the appearance ofa blue or green iris. The longer wavelengths (red, orange, yellow, and,in some cases, green) are absorbed by the thick layer of pigment on theback of the iris (known as the Iris pigment epithelium or “IPE”) beforethey have the opportunity to bend and backscatter. As a result, only theblue or green light is visible.

U.S. Pat. Nos. 6,306,127 and 8,206,379 disclose a procedure for alteringthe perceived color of a pigmented iris of a patient's eye. Thisprocedure comprises applying electromagnetic radiation to the anterioriris surface, thereby initiating the reduction and/or elimination of thestromal pigment covering all or a portion of such surface. Once thispigment is reduced and/or eliminated, white light is able to enter theiris and backscatter to create the appearance of a blue or green iris.

Patient satisfaction is an important feature of any medical procedure.In the case of aesthetic procedures, patient satisfaction depends inlarge part upon the ability of the physician to manage the patient'sexpectations by providing the patient with a reasonably accurateprediction of the aesthetic outcome of the procedure. In the case oflaser eye-color change, prediction is complicated by the occlusion ofthe stromal fibers by the stroma pigment. One option would be to performthe procedure on a small area of the iris behind the upper eyelid.Unfortunately, this is unlikely to provide an accurate prediction ofpost-operative color because a relatively large area of stromal fiberexposure is required to generate backscatter sufficient for a reasonablyaccurate prediction. Moreover, if any portion of the iris were treatedand the patient were to decide, based upon the predicted outcome, not toproceed with the procedure, the patient would be left with a discoloredarea on the iris (aka sectoral heterochromia).

The present invention predicts, prior to a laser iris color-changeprocedure, what a patient's iris color will be after the procedure. Thepresent invention does so by identifying and measuring a variety ofanatomical features of the patient's eye that affect or are otherwiserelevant to predicting the patient's post-operative iris color, derivinga post-operative iris color prediction from these measurements, andcommunicating this prediction to the patient in a manner sufficient tomanage the patient's expectations with respect to the aesthetic outcomeof the procedure. A preferred method of identifying and measuring atleast some of the anatomical features of the patient's eye is to usespecialized imaging and measurement devices and techniques, such asinfrared iris transillumination. A preferred method of deriving apost-operative iris color prediction from these measurements is tocompile a database of these measurements and their associated iriscolors from a relevant population pool and then compare the measurementscollected from the patient with the measurements contained in thedatabase to return a predicted iris color for the patient. Finally, apreferred method of communicating the predicted iris color to thepatient is to generate an image of the patient's face, replacing thepatient's pre-operative iris color with the predicted iris color (orcolors, if more than one result is returned from the database search).

Identifying and Measuring Anatomical Features

The invention comprises identifying and measuring a variety ofanatomical features of the patient's eye that affect or are otherwiserelevant to predicting the patient's post-operative iris color. Apreferred method of identifying and measuring at least some of theanatomical features of the patient's eye is to use specialized imagingand measurement devices and techniques. Following are examples of someof these anatomical features and some of the devices and techniquessuitable for identifying and measuring these features:

Iris Stroma—Thickness

Color comprises hue, saturation, and value. Hue can be defined as theattribute of a color by which it is discernible as a primary color orsome combination thereof, dependent upon its dominant wavelength(s), andindependent of its or their saturation or value. Saturation can bedefined as the intensity of a color, expressed as the degree to which itdiffers from white. Value can be defined as the brightness of color,defined by the amount of light it emits. In this respect, value may bethought of the inverse of saturation insofar as the more a color differsfrom white, the less light it will reflect, and vice versa.

The thickness of the iris stroma refers to the distance from itsanterior surface to its posterior surface, without regard to theanterior and posterior iris pigment layers. Iris stroma thickness isrelevant to predicting its post-operative hue. As explained above, thepost-operative iris stroma scatters incoming visible light into itscomponent wavelengths, each representing a different hue, and the longerwavelengths are absorbed by the IPE, while the shorter wavelengthsbackscatter anteriorly. The distance from the stroma fibers to the IPEis therefore relevant to predicting post-operative hue. When thisdistance is shorter, the IPE is more likely to absorb those wavelengthslonger than blue, thereby creating a blue iris. Where this distance islonger, the IPE is more likely to absorb those wavelengths longer thanblue and green, thereby creating a green iris.

Iris thickness may vary widely from the pupil to the limbus, dependingupon the dilation or constriction of the pupil. When a pupil dilates,the iris folds like an opening curtain, increasing variations in iristhickness. When a pupil constricts, the iris unfolds like a closingcurtain, reducing variations in iris thickness. The pupil can beconstricted by a variety of methods, including bright light and variousmedications, such as topical cholinergic agonists like Pilocarpine. Thethickness of a non-constricted iris may be determined at its thinnestpoint or at various locations. It can also be measured using theZhongshan Angle Assessment Program, which measures iris thickness at 750μm and 2000 μm from the scleral spurs and the maximum iris thickness atthe middle one third of the iris. Alternatively, the iris may beconstricted prior to measurement.

Iris thickness may, in embodiments of the invention, be imaged andmeasured using any number of devices and techniques, including opticalcoherence tomography or “OCT,” anterior segment optical coherencetomography or “ASOCT,” spectral domain optical coherence tomography or“SDOCT,” and ultrasound biomicroscopy or “UBM.”

Melanocytes and Lipofuscin—Location, Density, Color, and Thickness

There are generally two sources of pigment in the human eye: melanocytesand lipofuscin. Melanocytes are cells that produce pigmented granules ofmelanin called “melanosomes.” Melanosomes can be brown (called“eumelanin”) or yellow (called “pheomelanin”). Lipofuscin is apigmented, insoluble granule, typically yellowish brown in color,comprised of protein and lipid, that accumulates in cells as part of thenormal aging process or as the result of disease. Some commentators haveidentified lipofuscin as the waste product of oxidative metabolism,stored within each cell of the body and accumulated over time.

The location, density, color, and thickness of these pigments caninfluence post-operative iris color. Both types of pigment residethroughout the eye, but those most influencing post-operative iris colorreside inside the iris stroma. When the anterior stromal pigment isremoved from the iris, and the blue or green light is backscattered,pigments residing within the iris stroma can absorb this blue or greenlight, thereby diminishing the blue or green backscatter and permittingthe gray light reflected by the stroma fibers to appear moreprominently, resulting in a gray-blue or gray-green iris.

The greater the density of the pigments residing within the iris stroma,the greater the absorption of the blue or green backscatter, and thegreater the appearance of the gray fibers. In terms of color prediction,the greater the density of these intra-stromal pigments, the lower thesaturation and the higher the value.

The color of these intra-stromal pigments can also have a significanteffect on the post-operative iris color. The darker the pigments, themore they absorb the backscattered light, allowing more of the gray ofthe stromal fibers to show, thereby reducing saturation and increasingvalue. The lighter the pigments, the less they absorb the backscatteredlight, and the backscattered light overpowers the gray of the stromalfibers, thereby increasing saturation and reducing value

These pigments, particularly lipofuscin, can also reside in the aqueoushumor of the anterior segment and can coat and color the cornealendothelium. Again, depending upon the density and color of thesepigments, they can affect the perceived iris color. If the pigments aredenser and/or darker, they will absorb more of both the backscatteredlight and the grey of the stromal fibers, resulting in a post-operativeiris that is dull in hue, low in saturation, and low in value. If thepigments are less dense and/or lighter, they can also affect the hue ofthe post-operative iris, such as making a blue iris appear green ormaking a green iris appear more yellow-green.

Finally, the color, density, and thickness of the IPE can influence thepost-operative iris color. The darker, denser, and/or thicker the IPE,the more pronounced the limbal ring (which results from the IPE showingthrough the thin iris tissue at the limbus). In addition, the darker,denser, and/or thicker the IPE, the greater the absorption of the longerwavelengths, thereby affecting iris hue.

Pigment color, and/or density, and/or thickness may, in embodiments ofthe invention, be imaged and measured using any number of devices andtechniques, including optical coherence tomography or “OCT,” anteriorsegment optical coherence tomography or “ASOCT,” spectral domain opticalcoherence tomography or “SDOCT,” and ultrasound biomicroscopy or “UBM.”In the case of pigments coating or coloring the corneal endotheliumand/or residing in the aqueous humor of the anterior chamber, suchdevices and techniques also include a slit lamp or penlight examinationof the anterior chamber.

Iris Stroma Fibers—Physical Dimensions

The stroma fibers are responsible for the scattering, bending, andbackscattering of the visible light entering the iris post-operatively.Accordingly, the physical dimensions of these fibers are relevant to theprediction of the patient's post-operative iris color. These dimensionsinclude the thickness, density, axial periodicity, depth, andarrangement of these fibers. By way of example, the thicker and/ordenser the stromal fibers, the more gray light they reflect, and themore they occlude and/or absorb the backscattered light.

The physical dimensions of the iris stroma fibers may, in embodiments ofthe invention, be imaged and measured using any number of devices andtechniques, including optical coherence tomography or “OCT,” anteriorsegment optical coherence tomography or “ASOCT,” spectral domain opticalcoherence tomography or “SDOCT,” ultrasound biomicroscopy or “UBM,” andiris transillumination (using infrared or visible light).

Stromal Vasculature—Physical Dimensions

The stroma vasculature runs throughout the iris stroma, and the physicaldimensions of these vessels can influence the scattering, bending, andbackscattering of the visible light entering the iris post-operatively.Accordingly, the physical dimensions of these vessels are relevant tothe prediction of the patient's post-operative iris color. Thesedimensions include the thickness, density, axial periodicity, depth, andarrangement of these vessels. By way of example, the thicker and/ordenser these vessels, the more they occlude and/or absorb thebackscattered light.

The physical dimensions of the stromal vasculature may, in embodimentsof the invention, be imaged and measured using any number of devices andtechniques, including optical coherence tomography or “OCT,” anteriorsegment optical coherence tomography or “ASOCT,” spectral domain opticalcoherence tomography or “SDOCT,” ultrasound biomicroscopy or “UBM,” andiris transillumination (using infrared or visible light).

Anterior Chamber—Depth

The depth of the anterior chamber of the eye may vary significantly frompatient to patient. It generally varies between 1.5 and 4.0 mm andaverages 3.0 mm. The deeper the anterior chamber, the greater thepotential volume of pigment in the aqueous humor of the anteriorchamber, thereby potentially increasing the pigment effects describedabove. Accordingly, anterior chamber depth may be relevant to theprediction of the patient's post-operative iris color.

There are various methods of measuring anterior chamber depth, which maybe used in embodiments of the invention, including a slit lampexamination (using, for example, the Van Herick or Smith method),optical coherence tomography or “OCT,” anterior segment opticalcoherence tomography or “ASOCT,” spectral domain optical coherencetomography or “SDOCT,” ultrasound biomicroscopy or “UBM,” the penlightmethod, the Orbscan topograph system (Bausch & Lomb Surgical Inc.,Rancho Cucamonga, Calif., USA), the IOLMaster (Carl Zeiss Meditec, Jena,Germany), ultrasound (e.g., A-Scan, Alcon, Fort Worth, Tex., USA),Scheimpflug photography (e.g., Pantacam, (Oculus, Wetzlar, Germany), andsmartphone photography using the “EZ ratio.”

Cornea—Curvature and Clarity

The curvature and clarity of the cornea are also relevant to theprediction of post-operative iris color. The corneal curvature may beassociated with the anterior chamber depth, thereby influencing color asdescribed above. The corneal curvature also refracts the light enteringand exiting the iris stroma, thereby altering the light's path andpotentially affecting the perceived iris color. Finally, the clarity ofthe cornea may influence the saturation and value of the perceived iriscolor by limiting or permitting transmittance.

There are various methods of measuring corneal curvature, which may beused in embodiments of the invention, including the manual keratometer(e.g., Rodenstock, Munchen-Hamburg, Germany), the GalileiDual-Scheimpflug analyzer (Ziemer Group, Port, Switzerland), the cornealtopographer (e.g., Tomey TMS-1, Tomey, Phoenix, Ariz., USA), theautomated IOLMaster keratometer (Carl Zeiss GmbH, Oberkochen, Germany),optical coherence tomography or “OCT,” anterior segment opticalcoherence tomography or “ASOCT,” spectral domain optical coherencetomography or “SDOCT,” ultrasound biomicroscopy or “UBM,” the Orbscantopograph system (Bausch & Lomb Surgical Inc., Rancho Cucamonga, Calif.,USA), the IOLMaster (Carl Zeiss Meditec, Jena, Germany), ultrasound(e.g., A-Scan, Alcon, Fort Worth, Tex., USA), and Scheimpflugphotography (e.g., Pantacam, (Oculus, Wetzlar, Germany).

Corneal clarity may, in embodiments of the invention, be measured usingdigital imaging or corneal densitometry (e.g., Pentacam Scheimpflugdevice, Oculus Optikgerate GmbH, Wetzlar, Germany.

Iris—Curvature

Iris curvature is relevant to predicting post-operative iris colorbecause the curvature of the iris can influence the backscatter of theiris stromal fibers. Iris curvature may, in embodiments of theinvention, be imaged and/or measured using any number of devices andtechniques, including optical coherence tomography or “OCT,” anteriorsegment optical coherence tomography or “ASOCT,” spectral domain opticalcoherence tomography or “SDOCT,” and ultrasound biomicroscopy or “UBM.”

Deriving Color Prediction from Measurements

Once the anatomical features of the patient's eye relevant to predictingthe patient's post-operative iris color have been identified andmeasured, a reasonably accurate prediction must be derived therefrom. Apreferred method of deriving a post-operative iris color prediction fromthese measurements is to compile a database of these measurements andtheir associated iris colors from a relevant population pool and thencompare the measurements collected from the patient with themeasurements contained in the database to return a predicted iris colorfor the patient.

The database may comprise any combination of text, images, and/or otherdata. It may include a database management system or “DBMS,” maycomprise data in digital and/or analog form, may store and/or be locatedlocally or remotely to one or more of the remaining components of thepresent invention, may comprise one or more relational databases,operational databases, database warehouses, distributed databases,and/or end-user databases, may or may not be electronic, and may or maynot be networked. In the case of a computer database, the data mayreside in volatile memory and/or non-volatile memory.

The comparison of the measurements collected from the patient with themeasurements contained in the database may be accomplished using adata-processing device. The data-processing device is capable producinga defined set of outputs for a given set of inputs. It may operatemechanically and/or electronically, and its processing function maycomprise data format conversion, data verification, data validation,data sorting, data summarization, data aggregation, data analysis,and/or data reporting. Examples of data-processing devices includecomputers, calculators, central processing units (CPU), and graphicalprocessing units (GPU).

In one embodiment, the anatomical features of the patient's eye relevantto predicting the patient's post-operative iris color are identified andmeasured. A database has been compiled comprising measurements ofanatomical features relevant to iris color and images and/or other dataconcerning the iris colors associated with each such measurement. In asub-embodiment, this database is a relational database, in which theimages and/or data are arranged in a lookup table, one axis of which(i.e., either the rows or the columns) comprises ranges of measurements,and the other axis of which comprises images and/or other dataconcerning the iris colors associated with each such range. Adata-processing device then searches the database for images and/or datarelevant to the anatomical features of the patient's eye. In asub-embodiment, the search is conducted in Structured Query Language or“SQL,” such that each data point of the patient measurements isassociated with its range within the database lookup table, and a datamap of iris color categories is returned. See FIG. 1 for an exemplarydata map of a patient's perceived iris colors. This data map is thenconverted to a visual map, wherein an animated iris image is generated,which iris image comprises each of the perceived iris color categoriesof the patient iris, arranged as they appear in the patient's irisstroma. See FIG. 2 for an exemplary visual map of a patient's perceivediris color categories.

In another embodiment, the data and/or images of one or more patientsare stored in the database. In a sub-embodiment, pre-operative andpost-operative data and/or images of the same patients are captured andcompared to the predicted post-op color maps (data and/or visual maps).Where the pre-operative predictions and post-operative data and/orimages of a given patient are consistent (as defined by a predetermineddifferential tolerance), no changes are made to the database and/ordata-processing methodologies. Where the pre-operative predictions andpost-operative data and/or images of a given patient are not consistent,however, the database and/or data-processing methodologies are modifiedto improve the accuracy of iris color predictions. By way of example,the ranges for a given data point under a given iris color categorymight be modified. In yet another embodiment, pre-operative andpost-operative data and/or images of the same patients are captured andstored in the database in order to add more data points to the database,thereby improving its predictive power.

Communicating Prediction to Patient

Once the anatomical features of the patient's eye relevant to predictingthe patient's post-operative iris color have been identified andmeasured, a database is queried, and a reasonably accurate prediction isderived therefrom, the prediction must be communicated to the patient.In one embodiment, the prediction comprises a verbal or writtencommunication describing the range of possible iris colors. In anotherembodiment, the prediction comprises an image or series of images,featuring one or more post-operative iris color predictions. In yetanother embodiment, the prediction comprises an image or series ofimages of the patient's face, with his or her irides replaced withimages of one or more post-operative iris color predictions.

In one embodiment, a display device is used to present thepost-operative iris color predictions to the patient. The display devicecomprises any device that is capable of displaying images and/or otherdata in a format susceptible to human interpretation. The image and/orother data may appear in two- or three-dimensional form. Examples ofdisplay devices include photographs (digital and analog), digital files(e.g., .jpg, .jpeg, .tif, .tiff, .png, .pdf, .bmp, and .gif), digitalimage print-outs, cathode ray tube displays, light-emitting diodedisplays, electroluminescent displays, electronic paper, plasma displaypanels, liquid crystal displays, high-performance addressing displays,thin-film transistor displays, organic light-emitting diode displays,surface-conduction electron-emitter displays, field emission displays,laser TVs, carbon nanotubes, quantum dot displays, interferometricmodulator displays, digital microshutter displays, swept-volumedisplays, varifocal mirror displays, emissive volume displays, laserdisplays, holographic displays, or light field displays.

This disclosure of the invention has been presented for the purposes ofillustration and description. It is not intended to be exhaustive or tolimit the invention to the precise form described, and manymodifications and variations are possible in light of the teachingabove. The embodiments were chosen and described in order to bestexplain the principles of the invention and its practical applications.This description will enable others skilled in the art to best utilizeand practice the invention in various embodiments and with variousmodifications as are suited to a particular use. The scope of theinvention is defined by the claims contained in this Application, asamended.

What is claimed is:
 1. A method for generating predictions, at a timeprior to a laser iris color-change procedure, of what patients' iriscolor will be after the procedure is performed and its effects arerealized, the method comprising: capturing images of anatomical featuresof a patient's eye using a radiation-emitting device and an imagesensor, wherein the anatomical features comprise at least one of: aniris thickness; a density of iris stromal fibers; an axial periodicityof iris stromal fibers; a depth of iris stromal fibers; or anarrangement of iris stroma fibers; measuring the anatomical features ofthe patient's eye by extracting measurements from the captured images;generating search criteria based on the measurements of the anatomicalfeatures of the patient's eye; querying a database comprisingmeasurements of the anatomical features of a population of eyes and iriscolors associated with the anatomical features of the population of eyesusing the search criteria by comparing the search criteria with themeasurements of the anatomical features of the population of eyes andiris colors associated with the anatomical features of the population ofeyes contained in the database; generating a prediction of iriscolor-change based on a reduction or elimination of stromal pigment; andgenerating for display, on a display device, at least one of adescription or image of the prediction.
 2. The method according to claim1, wherein the anatomical features of the patient's eye further compriseat least one of: a location, density, color, or thickness of at leastone of melanocytes or lipofuscin; a thickness, density, axialperiodicity, depth, or arrangement of iris vasculature; an anteriorchamber depth; or a corneal curvature or clarity.
 3. The methodaccording to claim 1, wherein at least one of the radiation-emittingdevice or the image sensor comprises at least one of: optical coherencetomography; anterior segment optical coherence tomography; spectraldomain optical coherence tomography; or ultrasound biomicroscopy.
 4. Themethod according to claim 1, wherein displaying at least one of adescription or image of the prediction further comprises: generating adata map of a patient's iris colors; and converting the data map to avisual map featuring an animated iris image.
 5. The method according toclaim 1, wherein generating the prediction further comprises modifyingranges for a given data point under a given iris color category.
 6. Amethod for generating predictions, at a time prior to a laser iriscolor-change procedure, of what patients' iris color will be after theprocedure is performed and its effects are realized, the methodcomprising: capturing images of anatomical features of a patient's eyeusing a radiation-emitting device and an image sensor, wherein theanatomical features comprise at least one of: an iris thickness; adensity of iris stromal fibers; an axial periodicity of iris stromalfibers; a depth of iris stromal fibers; or an arrangement of iris stromafibers; measuring the anatomical features of the patient's eye, whereinmeasuring the anatomical features of a patient's eye comprises measuringan iris stroma thickness by determining a distance from a firstpredetermined plane of the patient's iris to a second predeterminedplane of the patient's iris; generating search criteria based onmeasurements of the anatomical features of the patient's eye; querying adatabase comprising measurements of the anatomical features of apopulation of eyes and iris colors associated with the anatomicalfeatures of the population of eyes using the search criteria; generatinga prediction of iris color-change based on a reduction or elimination ofstromal pigment by comparing the search criteria with the measurementsof the anatomical features of the population of eyes and iris colorsassociated with the anatomical features of the population of eyescontained in the database; and generating for display, on a displaydevice, at least one of a description or image of the prediction.
 7. Themethod according to claim 6, wherein at least one of theradiation-emitting device or the image sensor comprises at least one of:optical coherence tomography; anterior segment optical coherencetomography; spectral domain optical coherence tomography; or ultrasoundbiomicroscopy.
 8. The method according to claim 6, wherein the firstpredetermined plane of the patient's iris comprises a stroma fiber inthe patient's eye.
 9. The method according to claim 6, wherein the firstpredetermined plane of the patient's iris comprises an anterior surfaceof the patient's iris.
 10. The method according to claim 6, wherein thefirst predetermined plane of the patient's iris comprises an anteriorsurface of a stromal layer of the patient's iris.
 11. The methodaccording to claim 6, wherein the second predetermined plane of thepatient's iris comprises an anterior surface of the iris pigmentepithelium of the patient's eye.
 12. The method according to claim 6,wherein the second predetermined plane of the patient's iris comprises aposterior surface of the iris pigment epithelium of the patient's eye.13. The method according to claim 6, wherein the anatomical features ofthe patient's eye comprise location, density, color, or thickness of atleast one of melanocytes or lipofuscin.
 14. The method according toclaim 6, wherein the anatomical features of the patient's eye comprise athickness, density, axial periodicity, depth, or arrangement of irisvasculature.
 15. The method according to claim 6, wherein displaying atleast one of a description or image of the prediction further comprises:generating a data map of a patient's iris colors; and converting thedata map to a visual map featuring an animated iris image.
 16. Themethod according to claim 6, wherein generating the prediction furthercomprises modifying ranges for a given data point under a given iriscolor category.
 17. A non-transitory, computer readable mediumcomprising instructions recorded thereon, that when executed by one ormore processors cause operations comprising: capturing images ofanatomical features of a patient's eye using a radiation-emitting deviceand an image sensor, wherein the anatomical features comprise at leastone of: an iris thickness; a density of iris stromal fibers; an axialperiodicity of iris stromal fibers; a depth of iris stromal fibers; oran arrangement of iris stroma fibers; measuring the anatomical featuresof the patient's eye by extracting measurements from the capturedimages; generating search criteria based on the measurements of theanatomical features of the patient's eye; querying a database comprisingmeasurements of the anatomical features of a population of eyes and iriscolors associated with the anatomical features of the population of eyesusing the search criteria by comparing the search criteria with themeasurements of the anatomical features of the population of eyes andiris colors associated with the anatomical features of the population ofeyes contained in the database; generating a prediction of iriscolor-change based on a reduction or elimination of stromal pigment; andgenerating for display, on a display device, at least one of adescription or image of the prediction.
 18. The non-transitory, computerreadable medium according to claim 17, wherein the anatomical featuresof the patient's eye further comprise at least one of: a location,density, color, or thickness of at least one of melanocytes orlipofuscin; a thickness, density, axial periodicity, depth, orarrangement of iris vasculature; an anterior chamber depth; or a cornealcurvature or clarity.
 19. The non-transitory, computer readable mediumaccording to claim 17, wherein at least one of the radiation-emittingdevice or the image sensor comprises at least one of: optical coherencetomography; anterior segment optical coherence tomography; spectraldomain optical coherence tomography; or ultrasound biomicroscopy. 20.The non-transitory, computer readable medium according to claim 17,wherein displaying at least one of a description or image of theprediction further comprises: generating a data map of a patient's iriscolors; and converting the data map to a visual map featuring ananimated iris image.
 21. The non-transitory, computer readable mediumaccording to claim 17, wherein generating the prediction furthercomprises modifying ranges for a given data point under a given iriscolor category.